Most current workflow systems are non-dynamic (static) in nature. Once a workflow is defined (data ingestion → filtering → inference), it does not adapt when edge computing devices fail (e.g., GPUs overheat) or network conditions degrade. This article presents a ...
In the high-stakes world of IT infrastructure, the difference between a minor glitch and a major outage is often measured in minutes. Yet, for most organizations, the incident response lifecycle remains stuck in a manual era. As cloud environments grow...
Over the last two years, the artificial intelligence discussion has been preoccupied with scale. Larger models, more parameters and continually increasing infrastructure investment have been staged as the seemingly unavoidable future of enterprise AI. But within...
When I joined a B2B SaaS startup in 2021, I was transitioning from a bigger and more mature company. In my previous company, I was working on a particular area of the product – while it was rigorous and intense – I was excited...
Memory is what makes or breaks enterprise chat. Using your AI assistant will feel like a toy, not a production system, if it forgets who the user is, loses context between tickets, or asks the same clarifying questions every time. Naive methods that transmit the whole...
Disclaimer: Even though this blog post sounds harsh, I believe the people involved in the mainframe migration of TSB in 2018 acted always in good faith and with the best of the business and customers in mind. They acted according to the best knowledge available at the...
In today’s Financial Industry, performance of application is one of the most critical aspects. Whether it is a banking application dealing with millions worth of transactions, balance transfers or trading application dealing with time sensitive trades and orders or...
In our previous blog on regression analysis, we have discussed how machine learning models can predict continuous outcomes, such as house prices or sales revenue, based on input data. While regression models are powerful, their success depends heavily on the quality...
Regression is one of the most important techniques in predictive modelling. It is usually the gateway into the world of data science and machine learning, offering a perfect balance of simplicity and power. Whether you're forecasting next month's sales figures or...
As artificial intelligence continues to expand, the importance of effectively communicating with large language models (LLMs) is crucial. Whether you are a data scientist, business user, AI developer, or engineer, structuring and contextualizing...